Solvoyo and Enavate Announce Strategic Partnership to Accelerate ERP and AI Forecasting Solutions

Adopt a unified ERP and AI forecasting strategy now to boost agilidade within your operations and to deliver faster, data-driven decision-making.

Solvoyo and Enavate announce a strategic partnership that aligns ERP execution with AI forecasting across platforms and cloud-based tools, enabling 24×7 availability, flexibility, e um user-friendly experience that keeps data and insights available when teams need them.

Within the first 90 days, the joint solution will streamline ERP configuration and forecasting for clients in diverso industries, including retail, manufacturing, and distribution, while ensuring the platforms remain intuitive and that data pipelines are available to teams around the clock and across time zones.

khandelwal, a leader at Solvoyo, notes that the alliance gives credit to frontline teams by empowering them with real-time insights and simple workflows, boosting decision-making across finance and operations. These capabilities will help organizations respond to emerging demand and supply constraints while maintaining satisfaction with ERP and forecasting outcomes.

Define joint value, industry focus, and implementation approach

Adopt a joint value proposition by integrating Solvoyo’s predictive forecasting with Enavate’s ERP to reduce forecast errors, optimize purchasing, and accelerate value realization for small-business manufacturers and distributors. Target outcomes include a 15–25% uplift in forecast accuracy, 10–20% fewer stockouts, and a 10–15% improvement in working capital cycles within the first year. The solution is modular and fits into existing windows of planning cycles, enabling rapid deployment without disrupting current operations. Most impact occurs in manufacturing and high-variance distribution contexts where accurate demand signals directly narrow cash-to-cash cycle times. This collaboration can play a decisive role in shortening time-to-value for small-businesses that rely on planning accuracy.

Industry focus primarily targets manufacturing, wholesale distribution, and light assembly, with emphasis on small-business segments that manage multi-SKU portfolios. The joint offering uses predictive signals to adjust reorder points and safety stock and treats demand sensing, inventory optimization, and purchasing planning as a unified workflow. The platform uses cross-functional collaboration and dynamic planning to reduce cycle times. technavios reports indicate AI-driven forecasting within mid-market ERP ecosystems is expanding, aligning our collaboration with market demand and enhancing investors’ confidence. This approach targets critical points in the supply chain.

Implementation approach follows a four-stage plan: 1) discovery and data readiness, mapping ERP, WMS, and manufacturing data while establishing governance; 2) integration and model alignment, including API connections and SKU mapping; 3) pilot on a representative manufacturing line using ipad for shop-floor views and windows-based dashboards for planners; 4) scale with a documented rollout, change-management playbook, and a customisable set of dashboards and reports. This plan has been validated in pilot deployments and been refined with feedback from manufacturing teams. The rollout includes training and a detailed document that outlines governance, roles, responsibilities, and risk controls.

Governance, metrics, and next steps center on a joint steering group with representatives from Solvoyo and Enavate; define KPI thresholds (forecast accuracy, service level, inventory turns, days of inventory) and a single source of truth. The collaboration emphasizes a shared document repository for decisions, risks, and changes, and uses cloud-based infrastructure to support remote teams within a secure environment. The expected impact includes revolutionizing planning processes, improving purchasing and production alignment, and delivering measurable gains for small-business customers. This approach also strengthens investors’ perspective by demonstrating a scalable, repeatable model that delivers clear ROI.

ERP modernization roadmap enabled by Solvoyo and Enavate integration

Adopt a phased integration plan that unifies Solvoyo forecasting with Enavate ERP to unlock streamlined operations, gain measurable results, and establish a monthly cadence for billing and reportinganalytics across the entire organization.

This collaboration hinges on a clear partnership between Solvoyo and Enavate, a cross-functional team, and governance that aligns IT, finance, and operations. Currently available APIs and pre-built connectors enable faster start, reducing time-to-value and enabling the entire network to find better ways to operate.

The roadmap begins with a midsize-business pilot to test demand forecasting, inventory optimization, and digital billing alignment, with a focus on smoother billing cycles and faster reportinganalytics delivery. After proven success, extend to small sites and scale toward industry-specific configurations.

Key enablers include a unified data model, a streamlined network of data flows, and a set of ready-to-use solutions that deliver improved reportinganalytics dashboards and actionable insights. The integration supports extra data quality checks and better optimization of stock and capacity, driven by a customer-centric approach.

Measure success with monthly dashboards showing forecast accuracy, inventory turns, billing cycle time, and cost-to-serve. ROI depends on adoption speed, data cleanliness, and the depth of the digital integration; plan to realize gain in the first quarter and expand to the entire network by the next fiscal year.

In a manhattan hub, the combined platform reduces bottlenecks in reportinganalytics and strengthens collaboration across the industry. Partners find that the new path supports end-to-end operations, from planning to invoicing, with a single source of truth that is available to finance teams and field ops alike, boosting trust in the partnership and accelerating optimization.

AI forecasting capabilities tailored to demand planning and inventory optimization

Adopt ai-powered forecasting across the Solvoyo-Enavate platform to synchronize monthly demand planning with inventory optimization across distribution networks. Build a unified data fabric blending historical sales, promotions, seasonality, and supplier lead times to produce precise forecasts that drive purchase quantities, safety stock, and distribution allocations for small-business and wholesale segments, providing actionable insights for replenishment.

The research models use multiple signals–sales velocity, promotions, market events, and lead-time variability–to adapt to changing dynamics. This approach provides an overview of expected demand and inventory requirements, while reducing stockouts and excess stock by making planning decisions more data-driven across multiple warehouses. It focuses on optimizing service levels and inventory turns. The team collaborates to develop new models to capture micro-trends. Active research informs every forecast.

Enavate’s service layer ensures data quality and governance, enabling monthly scenario planning–base, optimistic, and conservative–and benchmarking forecast accuracy. The workflow includes ensuring data quality at every step. Integrations with e2open and coolgix keep supplier capacity and payment terms aligned, while dashboards on ipad give planners real-time reviews and quick actions.

Focus on measurable outcomes: forecast accuracy (MAPE, sMAPE), bias, service levels, fill rate, inventory turnover, and stockouts. Provide an overview of forecast performance to leadership and teams, with khandelwal providing interpretation and recommended improvements. This close loop between forecasting, planning, and purchasing, and it supports better payment cycles and cash-flow management.

For small-business models and broader distribution, the ai-powered forecast scales with the platform, enabling ongoing research, development, and refinements through the Solvoyo and Enavate alliance. Small teams benefit from streamlined workflows, monthly dashboards, and seamless integration with e2open and coolgix, all focused on quality service. Reviews from customers and field teams provide concrete input for ongoing improvement.

Data integration and governance for unified ERP analytics

Implement a centralized data fabric with clear lineage and automated validation to unify ERP analytics across departments. Appoint a chief data officer to drive governance, with data owners in finance, operations, procurement, inventory, and sales. Create a single source of truth by aligning master data including customers, suppliers, products, locations, and vendors. Define data models, naming conventions, and metadata tagging; implement an open-source data catalog or a vendor solution. Enable ai-powered data quality monitoring to detect anomalies and fix issues before they reach planning and reporting. Set access controls and encryption; ensure data is shared through APIs and secure pipelines, ensuring policy compliance across borders. Build a phased rollout with georgia office pilots and international teams before scaling to wholesalers and distributors. Develop a training program to upskill staff on data stewardship, quality checks, and standard reports. Use a demo dataset to validate use cases and measure optimization, including planning, forecasting, and inventory across departments.

Frame a pragmatic governance play that answers key questions: who identifies data issues, who approves changes, and how we measure impact across departments. Schedule quarterly reviews with the chief data officer and cross-functional leaders to adjust roles and policies. Lean on research-backed best practices to shape data contracts, data quality rules, and cross-border sharing. Plan for cross-system data feeds, versioning, and change management; specify data owners and escalation paths. Include both open-source and ai-powered components where possible to accelerate delivery while maintaining control. The governance playbook outlines roles, approvals, and data controls, and a quarterly demo shows progress to wholesalers, international teams, and other departments. Monitor metrics such as data availability, refresh latency, and user adoption across departments. georgia teams’ feedback loops ensure policies stay aligned with real-world needs.

Industry-specific use cases: manufacturing, retail, healthcare, and logistics

Start with a 90-day pilot in Massachusetts to validate cross-industry forecasting benefits, showing gains that attract investors and reassure customers. Integrate Solvoyo’s AI forecasting with Enavate’s ERP, and use a single reporting analytics dashboard to track entire value chains, including inputs from supplymint data feeds and open-source modules where appropriate.

• Fabrico

  • Improve forecast accuracy by 18–25% across key SKUs, reducing stockouts and excess inventory during peak periods. Use through API connections to pull data from supplier schedules and internal production planning to align capacity with demand signals.
  • Optimize master production schedules by simulating scenarios (capacity, supplier risk, and lead times) and sharing executive dashboards for quick decisions. Report that inventory turns rise and working capital needs tighten over the period.
  • Standardize data inputs from ERP and open-source analytics to deliver easy, repeatable forecasting workflows. Provide training videos for shop-floor teams to accelerate adoption and security controls to protect sensitive data.

• Retalho

  • Use forecasting to optimize assortments and promotions across channels, increasing margin opportunities while maintaining service levels. Link to Coupa for purchase planning to consolidate spend and reduce lead times.
  • Forecast demand at the store and regional level, then cascade to replenishment orders through the entire supply chain. Estimated improvements in stock coverage and on-shelf availability drive better customer experiences.
  • Leverage reporting analytics to monitor campaign lift, markdown effects, and seasonal demand shifts; publish executive-ready metrics to investors and partners.

• Cuidados de saúde

  • Forecast consumables and equipment demand to minimize shortages during period spikes, using historical usage data and real-time alerts. Ensure security and access controls for patient-facing inventory data while sustaining easy access for operations teams.
  • Coordinate with suppliers to align procurement with clinical demand, reducing waste and carrying costs. Use massachusetts-based facilities as pilots to demonstrate measurable improvements in service continuity.
  • Provide clinicians and administrators with open dashboards that combine utilization, cost, and outcome metrics, supported by reportinganalytics to inform procurement decisions and policy discussions with investors.

• Logística

  • Enhance warehouse throughput and last-mile reliability by forecasting arrival windows, dock readiness, and carrier capacity. Use throughputs and cycle times to optimize staffing and equipment utilization.
  • Planeie alterações na rede com o planeamento de cenários que considera a volatilidade da procura, os custos de combustível e as restrições das transportadoras. Meça os ganhos período a período na entrega atempada e a redução dos custos de envio expresso.
  • Publique dashboards operacionais que destaquem exceções, alertas de segurança e métricas de custo de serviço; forneça acesso a executivos e gestores de operações para uma tomada de decisão rápida.

O projeto de implementação enfatiza a governação multifuncional, o acesso aberto a dados para as equipas e as revisões executivas regulares. Alinhar os projetos-piloto com as oportunidades divulgadas publicamente pela pesquisa da Technavio e com os parâmetros de referência do setor, para definir metas e prazos realistas, mantendo ao mesmo tempo um olhar atento sobre o que os investidores esperam de soluções de ERP e de previsão escaláveis.

Cronograma de implementação, marcos e projeções de ROI para o cliente

Começar com um projeto-piloto de 12 semanas nos centros de distribuição internacionais e entre os associados para validar a precisão das previsões e o ROI antes da implementação em grande escala.

A implementação será orientada por um plano faseado que se foca primeiro na instalação e integração, e depois em testes práticos com dados reais de procura. Esta abordagem alimenta a confiança entre os líderes empresariais e ajuda os colaboradores a encontrar o equilíbrio certo entre a automatização e o juízo especializado. Abordamos as preocupações precocemente, definimos expectativas claras e fornecemos atualizações contínuas através de comunicações por e-mail e uma página de projeto dedicada para manter todos os intervenientes alinhados.

Durante a implementação, o sistema será configurado para uma capacidade de previsão melhorada que alimenta a tomada de decisões orientada para o crescimento. A implementação utiliza uma interface de tablet de fácil utilização para o pessoal do armazém e dashboards de ambiente de trabalho para os planeadores, com monitorização 24 horas por dia, 7 dias por semana, para detetar anomalias e acionar ações proativas. O âmbito internacional garante que as equipas de fornecimento, distribuição e instalação podem colaborar em tempo real, apoiadas pelas melhores práticas e por uma única fonte de informação fidedigna em todos os mercados.

Os principais marcos e entregáveis enfatizam os benefícios práticos: melhor visibilidade do inventário, ciclos de decisão mais rápidos e colaboração otimizada entre os colaboradores de diversas funções. Para manter o ímpeto, mantemos a instalação simples e focamo-nos primeiro em módulos de alto impacto, expandindo depois para uma cobertura mais ampla assim que os resultados comprovarem o valor da parceria.

As projeções de ROI baseiam-se numa abordagem disciplinada e orientada por dados. Esperamos que a previsão aprimorada reduza ruturas de stock e inventário obsoleto, melhore os níveis de serviço e diminua as cargas de trabalho manuais nas equipas de distribuição, produção e vendas. Os seguintes cenários fornecem uma visão prática para os decisores ao decidirem os próximos passos. As premissas incluem um projeto piloto de 3 regiões e 6 locais com uma contagem de SKU base modesta e um custo de manutenção padrão de 20% no inventário médio. O aumento nos sinais de procura será suportado por uma previsão orientada por IA, com dispositivos tablet que permitem à equipa de campo agir em tempo real com base nas informações.

As premissas subjacentes ao modelo de ROI incluem um layout de distribuição de 3 regiões, 6 locais e 100.000 SKUs com variabilidade da procura sazonal. A precisão da previsão melhora 15–25%, as ruturas de stock diminuem 30–40% e os custos de manutenção diminuem à medida que o inventário é alinhado com a procura real. A estrutura também contabiliza a monitorização 24×7, alertas proativos por e-mail e um processo de instalação simplificado que minimiza a interrupção das operações durante o arranque. O resultado é um caminho prático para uma melhoria mensurável nas métricas de negócios, com um ponto de decisão claro para escalar com base nos ganhos observados e no feedback de associados internacionais. A página de atualizações do projeto mantém todos informados, e o combustível para o crescimento contínuo vem de melhorias contínuas no planeamento do aprovisionamento, na eficiência da distribuição e em interfaces fáceis de usar que capacitam as equipas a decidir de forma rápida e precisa.